AIエージェントの能力を拡張するClaudeスキルの完全なコレクションをご覧ください。
Generates standardized, actionable operational runbooks for incident response, system maintenance, and troubleshooting procedures.
Implements efficient asynchronous programming and reactive data streams using Kotlin coroutines and Flow in Android applications.
Implements structured Git branching models and naming conventions to create a clear, professional narrative of the software development lifecycle.
Architects structural page layouts using Atomic Design principles to create reusable, content-agnostic frontend skeletons.
Configures automated Sentry alerts, triages software issues, and manages cross-platform notification workflows to maintain system reliability.
Constructs complex, standalone UI sections like headers and dashboards by aggregating atoms and molecules.
Implements structured note-taking patterns and AI-specific annotations to preserve context and development rationale within codebases.
Establishes bidirectional links between source code and documentation to preserve architectural context and maintain artifact synchronization.
Builds, trains, and optimizes sophisticated deep learning models using TensorFlow and the Keras API.
Builds sophisticated node-based editors using custom React Flow components, handles, and interactive edges.
Architects foundational design tokens and CSS primitives to establish a consistent, scalable design system using sub-atomic principles.
Facilitates professional Behavior-Driven Development (BDD) workflows to align developers, testers, and business stakeholders through structured discovery.
Generates systematic diagnostic procedures and operational runbooks for resolving complex software and infrastructure issues.
Streamlines the initialization and configuration of autonomous AI agents using the Claude Agent SDK.
Configures and manages secure encryption backends and secret storage providers for the Fnox ecosystem.
Monitors GitLab CI/CD pipelines and jobs in real-time, providing status updates and automated failure diagnostics.
Streamlines monorepo development with standardized CI/CD patterns, automated version management, and optimized cross-package development strategies.
Transforms research taxonomies into rigorous, evidence-first outlines for technical papers and structured documentation.
Audits research outlines by analyzing evidence coverage and mapping redundancy to ensure a structured, verifiable foundation.
Integrates relevant citations into technical drafts to meet diversity targets without altering factual content or introducing new claims.
Audits workspace completeness by verifying required pipeline artifacts and unit outputs against defined contracts.
Generates seamless, content-driven transitions between research subsections to ensure narrative coherence without introducing new factual claims.
Defines verifiable, evidence-linked table schemas for research papers and surveys to ensure high information density and data integrity.
Analyzes research pipelines for evidence gaps and generates actionable recovery plans to prevent hollow writing.
Generates structured, evidence-grounded peer review reports and referee feedback based on extracted research claims and evidence gaps.
Assembles per-section research prose into a unified draft while preserving structure and injecting transitions.
Generates concise, high-signal literature snapshots using a bullet-first methodology and evidence-based citation management.
Generates structured writing briefs and intent cards for research subsections to ensure evidence-driven, prose-free drafting.
Generates structured, evidence-rich context packs to bridge research artifacts and high-quality technical drafting.
Streamlines research paper collections by deduplicating entries and ranking them to create high-quality core datasets for academic analysis.
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